Systems and methods for managing regimen adherence

ABSTRACT

Systems and methods are provided for managing medical adherence. An exemplary method may include managing medical adherence utilizing data aggregating and processing to determine impact on a user&#39;s health based on their behavior related to prescribed medication. The method may entail utilizing data related to a medication regimen and patient behavior to determine a patient&#39;s compliance to the regimen in terms of dosage and time. These values may be utilized to calculate a medical adherence value representing a patient&#39;s adherence to a prescribed regimen. Responsive to determining low medical adherence, a notification may be generated which may result in an intervention with the patient.

CROSS-REFERENCE TO RELATED APPLICATIONS

This Application claims the benefit of priority from ProvisionalApplication No. 61/839,528, entitled “Systems and Methods for ManagingPatient Conditions,” filed Jun. 26, 2013, which is incorporated hereinby reference in its entirety.

TECHNICAL FIELD

Various embodiments of the present disclosure relate generally tomanaging medical adherence. More specifically, particular embodiments ofthe present disclosure relate to systems and methods for managingmedical adherence utilizing data aggregation and processing the data todetermine impact on a patient's health based on their behavior relatedto a prescribed medication.

BACKGROUND

An important aspect of medical care is medication management. In fact,medication adherence, that is, a patient's utilization of the prescribedregimen of medication on time and in the correct dosage, is directlyrelated to the success of the treatment or management of a medicalcondition. For example, organ transplant patients may be prescribedpills in the order of 30-50 per day that have to be consumed at specifictimes through the day. Inconsistency in adherence to the prescribedregimen may have serious short-term and long-term consequences, such asorgan rejection or even death Mismanagement of regimens associated withother medical conditions, such as HIV, allergies, diabetes, asthma,hypertension, may also lead to similar consequences that range fromcausing discomfort to being lethal.

Typically, various health service provides, provide “pill-box” typeresources to monitor medication adherence. These resources are limitedto providing users with reminders of the medicine they have taken orsimply keeping a record of actions related to compliance with amedication regimen.

However, it can be difficult for a healthcare provider to efficientlymanage a patient's medical adherence utilizing such an approach toimprove a patient's health or clinical outcomes.

SUMMARY OF THE DISCLOSURE

Embodiments disclose systems and methods for managing a patient'smedical adherence, specifically adherence to medication.

According to some embodiments, computer-implemented methods aredisclosed for managing a patient's medical adherence. In an exemplarymethod, the method includes receiving data related to the patient, thedata including information related to a medication regimen associatedwith the patient that includes one or more medications, patient behaviordata, a respective literacy level associated with each of the one ormore medications. The method further includes calculating a complianceto dosage and a compliance to time for each of the one or moremedications based on the received data and, thereafter, calculating adrug adherence count associated with each of the one or more medicationsby summing at least two of the compliance to dosage, the compliance totime, and the respective literacy level associated with each of the oneor more medications. The method may also include determining a dailymedication adherence for each of the one or more medications,calculating a daily regimen adherence value by summing the dailymedication adherence of all of the one or more medications in themedication regimen, calculating a daily regimen baseline value byre-calculating the daily regimen adherence value by utilizing a maximumpotential value for the drug adherence count for each of the respectivemedications in the regimen associated with the patient. The method mayfurther include, determining a medical adherence value based on thedaily regimen adherence value and the daily regimen baseline value, andcomparing the medical adherence with a threshold value.

According to some embodiments, systems are disclosed for managing apatient's medical adherence. One system includes a memory havingprocessor-readable instructions stored therein and a processorconfigured to access the memory and execute the processor-readableinstructions, which when executed by the processor configures theprocessor to perform a method. In an exemplary method, the methodincludes receiving data related to the patient, the data includinginformation related to a medication regimen associated with the patientthat includes one or more medications, patient behavior data, arespective literacy level associated with each of the one or moremedications. The method further includes calculating a compliance todosage and a compliance to time for each of the one or more medicationsbased on the received data and, thereafter, calculating a drug adherencecount associated with each of the one or more medications by summing atleast two of the compliance to dosage, the compliance to time, and therespective literacy level associated with each of the one or moremedications. The method may also include determining a daily medicationadherence for each of the one or more medications, calculating a dailyregimen adherence value by summing the daily medication adherence of allof the one or more medications in the medication regimen, calculating adaily regimen baseline value by re-calculating the daily regimenadherence value by utilizing a maximum potential value for the drugadherence count for each of the respective medications in the regimenassociated with the patient. The method may further include, determininga medical adherence value based on the daily regimen adherence value andthe daily regimen baseline value, and comparing the medical adherencewith a threshold value.

According to some embodiments, a non-transitory computer readable mediumis disclosed as storing instructions that, when executed by a computer,cause the computer to perform a method, the method includes receivingdata related to the patient, the data including information related to amedication regimen associated with the patient that includes one or moremedications, patient behavior data, a respective literacy levelassociated with each of the one or more medications. The method furtherincludes calculating a compliance to dosage and a compliance to time foreach of the one or more medications based on the received data and,thereafter, calculating a drug adherence count associated with each ofthe one or more medications by summing at least two of the compliance todosage, the compliance to time, and the respective literacy levelassociated with each of the one or more medications. The method may alsoinclude determining a daily medication adherence for each of the one ormore medications, calculating a daily regimen adherence value by summingthe daily medication adherence of all of the one or more medications inthe medication regimen, calculating a daily regimen baseline value byre-calculating the daily regimen adherence value by utilizing a maximumpotential value for the drug adherence count for each of the respectivemedications in the regimen associated with the patient. The method mayfurther include, determining a medical adherence value based on thedaily regimen adherence value and the daily regimen baseline value, andcomparing the medical adherence with a threshold value.

Additional objects and advantages of the disclosed embodiments will beset forth in part in the description that follows, and in part will beapparent from the description, or may be learned by practice of thedisclosed embodiments. The objects and advantages of the disclosedembodiments will be realized and attained by means of the elements andcombinations particularly pointed out in the appended claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate various exemplary embodiments andtogether with the description, serve to explain the principles of thedisclosed embodiments.

FIG. 1 is a schematic diagram of a network environment for managingmedical adherence, according to an embodiment of the present disclosure.

FIG. 2 is a flow diagram of an exemplary method for managing medicaladherence, according to an embodiment of the present disclosure.

FIGS. 3A and 3B illustrate an exemplary implementation of calculatingthe regimen number and assigning unique identification numbers,according to an embodiment of the present disclosure.

FIG. 4 is a flow diagram of an exemplary method for calculatingcompliance with dosage, according to an embodiment of the presentdisclosure.

FIG. 5 is a flow diagram of an exemplary method for calculatingcompliance with time, according to an embodiment of the presentdisclosure.

FIG. 6 is a block diagram of an exemplary computer system in whichembodiments of the present disclosure may be implemented.

DESCRIPTION OF THE EMBODIMENTS

While the present disclosure is described herein with reference toillustrative embodiments for particular applications, it should beunderstood that embodiments of the present disclosure are not limitedthereto. Other embodiments are possible, and modifications can be madeto the described embodiments within the spirit and scope of theteachings herein, as they may be applied to the above-noted field of thepresent disclosure or to any additional fields in which such embodimentswould be of significant utility.

In the detailed description herein, references to “one embodiment,” “anembodiment,” “an example embodiment,” etc., indicate that the embodimentdescribed may include a particular feature, structure, orcharacteristic, but every embodiment may not necessarily include theparticular feature, structure, or characteristic. Moreover, such phrasesare not necessarily referring to the same embodiment. Further, when aparticular feature, structure, or characteristic is described inconnection with an embodiment, it is submitted that it is within theknowledge of one skilled in the art to effect such feature, structure,or characteristic in connection with other embodiments whether or notexplicitly described.

In view of the challenges associated with the conventional techniquesoutlined above, systems and methods are disclosed herein for managingmedication adherence.

Reference will now be made in detail to the exemplary embodiments of thedisclosure, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the drawings to refer to the same or like parts.

FIG. 1 is a schematic diagram of an exemplary network environment inwhich various systems may manage and monitor medical adherence,according to an embodiment of the present disclosure. As shown in FIG.1, the environment may include a plurality of user or client devices 102that are communicatively coupled to each other as well as one or moreserver systems 106 via an electronic network 100. Electronic network 100may include one or a combination of wired and/or wireless electronicnetworks. Network 100 may also include a local area network, a mediumarea network, or a wide area network, such as the Internet.

In one embodiment, each of user or client devices 102 may be any type ofcomputing device configured to send and receive different types ofcontent and data to and from various computing devices via network 100.Examples of such a computing device include, but are not limited to,mobile health devices, a desktop computer or workstation, a laptopcomputer, a mobile handset, a personal digital assistant (PDA), acellular telephone, a network appliance, a camera, a smart phone, anenhanced general packet radio service (EGPRS) mobile phone, a mediaplayer, a navigation device, a game console, a set-top box, a biometricsensing device with communication capabilities, or any combination ofthese or other types of computing devices having at least one processor,a local memory, a display (e.g., a monitor or touchscreen display), oneor more user input devices, and a network communication interface. Theuser input device(s) may include any type or combination of input/outputdevices, such as a keyboard, touchpad, mouse, touchscreen, camera,and/or microphone.

In one embodiment, each of the user or client devices 102 may beconfigured to execute a web browser, mobile browser, or additionalsoftware applications that allows for input from patients and otherindividuals from the medical field including physicians, nurses,pharmacists, etc. One or more of user or client devices 102 may befurther configured to execute software allowing for monitoring ofpatient behavior including the ability to receive user input orutilizing associated sensors to monitor patient behavior. For example,user or client devices 102 may contain an application which allows it toreceive data from a paired and/or integrated blood sugar level monitorand then transmit the data to other entities within environment 100.Alternatively, user or client devices 102 may contain applications whichallow for a patient to input information related to patient behaviorsuch as consumption of medication, including, but not limited to, dosageand/or compliance information.

Server system 106 in turn may be configured to receive data related to amedication regimen, individual medications in a medication regimen,patient, patient behavior, etc. It should be noted that while a singularserver system 106 is described, method 200, described below with respectto FIG. 2, may be implemented using a plurality of server systemsworking in combination, a single server device, or a single system.

Also, as shown in FIG. 1, server system 106 may include one or moredatabases 108. In an embodiment, databases 108 may be any type of datastore or recording medium that may be used to store any type of data.For example, databases 108 may store data received by or processed byserver system 106 including information related to a patient'sprescribed regimen, including timings and dosages associated with eachmedication of the regimen. Databases 108 also may store informationrelated to the patient including their literacy level related to each ofthe prescribed medications.

Additionally, as shown in the example of FIG. 1, server system 106 mayinclude processor 110, In an embodiment, processor 110 may be configuredto execute a process for managing medical adherence. The managementprocess may, for example, continue to constantly monitor regular (e.g.,daily, weekly, monthly, etc.) compliance to time and dosage of a medicalregimen. Utilizing these values along with additional factors, metricsmay be generated which efficiently indicate a patient's overalladherence to a medication regimen.

In an embodiment, processor 110 may be configured to receiveinstructions and data from various sources including user or clientdevices 102 and store the received data within databases 108. In someimplementations, any received data may be stored in the databases 108 inan encrypted form to increase security of the data against unauthorizedaccess and complying with HIPAA privacy regulations. Processor 110 orany additional processors within server system 106 also may beconfigured to provide content to client or user devices 102 for display.For example, processor 110 may transmit displayable content includingmessages or graphic user interfaces soliciting information related topatient behavior.

FIG. 2 is a flow diagram of a method 200 for managing a patient'smedical adherence, according to an embodiment of the present disclosure.

In step 202, method 200 includes receiving data related to the patient.For example, this data may be received and/or retrieved by processor 110from one or more databases 108 or may be directly received from one ormore user or client devices 102. The data may include informationrelated to a medication regimen associated with the patient thatincludes one or more medications, patient behavior data (e.g. objectiveand subjective data), a respective literacy level associated with eachof the one or more medications, and a respective drug importance factorassociated with each of the one or more medications. This received datamay previously be generated utilizing processor 110 and stored indatabases 108. Alternatively, the received data may be transmitted byone of user or client devices 102, including data previously transmittedand stored in databases 108. In embodiments, one of user or clientdevise 102 may transmit data in real time, continuously, periodically,or based on a predetermined duty cycle.

In embodiments, information related to a medication regimen, may includeinformation regarding all the medicine included in the regimen includingprescribed dosage and times related to the medication.

In additional embodiments, this information may include uniqueidentities assigned to the regimen and unique identities assigned toeach of the one or more medications in the regimen allowing for easiermanagement of data. For example, in the case of multiple diseases forwhich a patient may be treated, regimen identities may be assigned bymultiples of 100. For example, a first disease regimen number may be100, a second disease regimen number may be 200, and henceforth. Asdiscussed earlier, each regimen may contain one or more medicationsprescribed by a physician. Each medication in a regimen may be assigneda unique number for identification. For example, D[i,j], D[i,j+1] D[i,n#i], where Medication ID=subscript 1, subscript 2. Here, Here subscript1 (e.g., i) refers to the regimen number and subscript 2 (e.g., j, j+1,. . . ) refers to the ID of the medication in the same regimen. Theregimen numbers may be assigned in incremental manner sequentiallystarting from first regimen of the patient.

Accordingly, while data related to a medical regimen may be capturedbased on the original medication name, the data may be managed in aneasier manner by assigning each medication a unique identity utilizingthe naming convention discussed above. In some embodiments, othersuitable name/identifying conventions may be used with the principle ofthis disclosure.

For example, FIGS. 3A and 3B illustrate an exemplary implementation ofcalculating the regimen number and assigning unique identificationnumbers, according to an embodiment of the present disclosure. Step 308entails assigning each respective disease a unique disease number,disease 310 (HIV) is assigned a “1,” disease 311 (diabetes) is assigneda “2,” and disease 312 (cancer) is assigned a “3.” Thereafter, in step304, each of the assigned numerical values are multiplied by 100 toproduce disease regimen numbers 314, 316, and 317 for the respectivediseases. The disease numbers from step 304 are then utilized tocalculate medication number in step 306. Step 306 is illustrated in moredetail in FIG. 3B. Using the disease regimen numbers 314, 316, and 317,the mediation numbers are calculated by incrementally adding anincremental integer value to the disease number starting with 1 for eachrespective medication associated with the regimen. For example, fordisease 310 (HIV), for a first medication 320 (Comibir) associated withdisease regimen number 314, a 1 is added to 100 to calculate amedication number value of 101. For a second medication 321 associatedwith disease regimen number 314, a 2 is added to 100 to calculate amedication number value of 101. The medication numbers for medications322, 323, 324, and 325 are similarly calculated based on theassociations of these medications with respective disease regimens 316and 817. In some embodiments, these values then may be stored indatabases 108.

In embodiments, patient behavior data may refer to data related topatient behavior including when and if a patient complied withrecommendations of a regimen For example, patient behavior data mayindicate that a patient orally consumed a certain dosage of medicationat various specific times such as 8 a.m., 2 p.m., and 8 p.m. daily.

In embodiments, literacy level (LL) is a metric to assess thefamiliarity of a patient with a prescribed regimen and its medications.This value may be calculated or updated based on various conditions. Ina first exemplary condition, a patient may be asked to take a surveywith questions related to literacy regarding medical adherence for theunique regimen. This survey or observations by a physician regarding apatient's knowledge base may be utilized to set the baseline literacylevel for a patient's particular regimen. The score based on a survey ora physician's observations may be updated subsequently based onadditional surveys or observations. In a second exemplary condition, theliteracy level may be impacted by determination that erroneousmedication data was entered by a patient using user or client device 102a threshold amount of times over a particular period. For example, inmonitoring daily medication adherence over a week, it may be determinedthat the patient entered erroneous medication data or did not enter anymedication data a threshold amount of times in the week. Thereafter, theassigned literacy level to the regimen may be dropped. In a thirdexemplary condition, the literacy level may be impacted based onoccurrence of a condition based on lack of medical adherence by apatient. For example, if there are any ill effects based on userbehavior, such as lowering of blood sugar levels due to missingmedication.

In embodiments, intervention techniques, such as changing the types ofmedicine or motivational interviews with patients, may be applied inresponse to determination of low literacy levels, Motivationalinterviews may include a physician (or other medical professional)speaking with a patient, discussing benefits of following the regimen,and explaining impact of failure to do so. Thereafter, levels of error,ill effects, and survey results may be reassessed after a certain timeperiod, such as daily, weekly, monthly basis.

In embodiments, drug importance factor (DIF) may be entered by a medicalprofessional (e.g., physician, pharmacist, physician's assistant, etc.)associated with a patient's medical regimen utilizing a user or clientdevice 102. This value may allow for defining a relative importance of agiven medication with respect to other medications in the same regimenfor a specific patient or disease being treated. In detail, data relatedto the assignment of drug importance factors may be assigned by aphysician during medication validation. While a physician may utilize acomparison or relativity in their thought process for assigning the drugimportance factor, each medication in a regimen is assigned a drugimportance factor without any contingency on any other medication. As anexample, a physician may be provided with a data entry field next toeach medication to weigh its importance for the prescribed regimen, on ascale of 1 to 3. In such an example, it is possible for all medicationsin a regimen to get an assigned value of 3 each if found important.Alternatively, any suitable scale may be used which is consistence withthe principle of the present disclosure. However, in embodiments, aminimum of 1 is assigned in order to ensure all medications obtain anon-zero value for the purposes of being able to calculate a dailymedication adherence as is discussed in further details below.

In an additional embodiment, for calculating the drug importance factor(DIF), the rationale behind a physician's drug importance factor scoringmay be partially supplemented by using pharmacokinetic techniques. Thedrug importance factor baseline may be based on clinical data or set bya certified pharmacologist by examining interrelationships betweenmedications and hence their effects on similar patients.

In step 204, method 200 includes calculating a compliance to dosage anda compliance to time for each of the one or more medications based onthe received data.

Regarding compliance to dosage, this value may be calculated utilizingexemplary method 400. In step 402, step 400 includes determiningprescribed dosage for each of the one or more medications based on thereceived data. That is, the presence disclosure contemplates utilizinginformation regarding the prescribed regimen to determine dosageassociated with each of the one or more medications. For example, thismay be based on the prescription information input by a physician or aphysician's assistant in-charge of providing medical services to apatient.

In step 404, method 400 includes assigning boolean (or binary) valuesfor actual dosage consumed based on the prescribed dosage and receiveddata related to patient behavior. For example, data associated withpatient behavior may indicate whether a patient consumed a particularprescribed dosage. Accordingly, in an exemplary embodiment, when adosage is consumed, a value of “1” may be assigned, while when a dosageis not consumed a value of “0” might be assigned. Since, a patient mayconsume an inaccurate amount of the prescribed dosage, differentthresholds may be assigned regarding whether a partial consumption leadsto an assignment of “1” or “0” value. For example, if a dosage of threepills of a first medication is assigned and the patient consumes onlytwo out of the three pills, a boolean may be assigned a “1” if athreshold value is preset so that anything higher than a 60% consumptionof a dosage is considered to be compliant. This threshold amount may bepreset by a medical professional taking into account in the importanceof the medicine, impact on variations in dosage, and other additionalfactors.

In step 406, method 400 includes calculating compliance to dosage foreach of the one or more medications utilizing the assigned booleanvalues. For example, for ten dosages prescribed throughout the day, theboolean values may be utilized to calculate an overall value for theday. For example, if 8 out of 10 prescribed dosages for a particularmedication where complied with throughout the day, then the actualconsumed dosage would be assigned a “1” for those 8 instances and a “0”would be assigned for the other two instances. Accordingly, a compliancevalue of 0.8 may be calculated for the compliance to dosage for thatparticular medicine by dividing the overall boolean value with the totalprescribed instances.

In additional embodiments, the compliance to dosage may simply be aratio of dosage consumed to total dosage prescribed. For example, if apatient was prescribed 10 units of a medication in a day and took only 8units, then the respective compliance to disease is obtained by dividingthe amount of units actually consumed by the prescribed units. In thisinstance, it would be 8/10 which equals 0.8.

Compliance to dosage may provide valuable information about a patientsbehavior. For example, an indication regarding a trend in a rise or dropof medication taken may be very significant for certain patients, suchas patients on a short acting insulin regimen to control their diabetes.

Regarding compliance to time, this interaction may be calculatedutilizing exemplary method 500. In step 502, method 500 includesdetermining prescribed dosage time for each of the one or moremedications based on the received data. That is, utilize informationregarding the prescribed regimen to determine the time when each of theone or more medications is to be consumed. For example, this may be theprescription information input by a physician or a physician's assistantin-charge of providing medical services to a patient.

In step 504, method 500 includes assigning boolean (or binary) valuesfor actual consumption time based on the prescribed dosage time andreceived data related to patient behavior. For example, data associatedwith patient behavior may indicate the time a patient consumed aparticular dosage. Accordingly, in an exemplary embodiment, when adosage is consumed at the correct time, a value of “1” may be assigned,while when a dosage is not consumed at a prescribed time, a value of “0”might be assigned. Since, a patient may not always consume the medicineat the prescribed time, a threshold amount of time may be set which isconsidered as still complying with the regimen. For example, if athreshold of 15 minutes is set, then if the patient consumes a dosagefifteen minutes before or after a prescribed time of 6 p.m., theconsumed dosage may be considered to be complying with the prescribeddosage time. The threshold amount of time may be preset by a medicalprofessional taking into account in the importance of the medicine,impact on variations in dosage, and other additional factors including,but not limited to availability of the prescribed medication.

In step 506, method 500 includes calculating compliance to time for eachof the one or more medications utilizing the assigned boolean values.For example, for ten dosages prescribed throughout the day, the booleanvalues may be utilized to calculate an overall value for the day. Forexample, if 8 out of 10 actual consumption times for a particularmedication complied with the prescribed dosage times, then the actualconsumption time would be assigned a “1” for those 8 instances and a “0”would be assigned for the other two instances. Accordingly, a compliancevalue of 0.8 may be calculated for the compliance to time for thatparticular medicine by dividing the overall boolean value with the totalinstances.

In additional embodiments, the compliance to time may simply be afunction of the time delays associated with consumed dosages. Forexample, the prescribed times for dosages may be utilized as a baseline,and every instance of non-compliance of time related to a dosage mayresult in a drop in the compliance to time value. In embodiments, thedrops in a compliance to time value may be proportional to the timedelays and/or early consumption.

In some embodiment, the compliance to time may be a function of timesand dosage. For example, consumption of a prescribed amount ofmedication at the suggested time would count as 100 percent compliancefor that instance. However, a five minute delay may count as 75%compliance, a ten minute delay may count as 50% compliance, and so onand so forth, until a time when the prescribed dose is considered tohave zero percent compliance. The times for the percent of compliancemay be set based on pharmaceutical and clinical research associated withthe effectiveness of a medication, and other factors. For example, ifinsulin is to be injected by a diabetes patient at 2 p.m. with anexpectation of a meal to be consumed at 2:30 p.m., then injecting it at2:30 p.m. may not have the desired impact that injecting it on schedulewould have.

With reference to FIG. 2, in step 206, method 200 further includescalculating a drug adherence count (DAC) associated with each of the oneor more medications. In detail, the drug adherence count may becalculated by summing at least two of the compliance to dosage (CD), thecompliance to time (CT), and the respective literacy level (LL)associated with each of the one or more medications. In embodiments, thedrug adherence count may be calculated by summing all three of thecompliance to dosage (CD), the compliance to time (CT), and therespective literacy level (LL) associated with each of the one or moremedications.

In embodiments, drug adherence count (DAC) serves as a metric thatefficiently accounts for a consumed medication including compliance withrespective prescribed time of the day when it is supposed to be taken,compliance with respective prescribed dosage of the medication, and apatient's literacy about the medications the regimen. In an exemplaryembodiment, the calculation of DAC may be presented in an equation asfollows:

DAC=CD+CT+LL

In step 208, method 200 includes determining a daily medicationadherence (DDA) for each of the one or more medications based on thedrug adherence count (DAC) and the drug importance factor (DIF)associated with each of the one or more medications. In embodiments, thedaily medication adherence is determined by multiplying the drugadherence count by the drug importance factor associated with each ofthe one or more medications. In embodiments, daily medication adherenceis a metric which aids in efficiently indicating adherence towards theproscribed regimen by adding relative weightage to medication that isconsidered more relevant or important. Continuing the example from step206, the calculation for determining the DDA may be presented in anequation, as follows:

DDA=DAC×DIF

In step 210, method 200 includes calculating a daily regimen adherence(DRA) value by summing the daily medication adherence of all of the oneor more medications in the medication regimen. In embodiments, allowingfor the summing of the daily medication adherence for each of the or theor more medications in a regimen, allows for a singular value whichefficiently represents adherence for the whole regimen. This allows foran efficient and quick monitoring of a prescribed regimen, instead ofstraining resources, such as time, to look at compliance for eachindividual medication.

Continuing the example from step 208, the daily regimen adherence (DRA)is a sum of DDA for medications D[i,j], D[i,j+1] D[i,n #i].

In step 212, method 200 includes calculating a daily regimen baselinevalue (DRB) by re-calculating the daily regimen adherence value byutilizing a maximum potential value for the drug adherence count foreach of the respective medications in the regimen associated with thepatient. Accordingly, the daily regimen baseline value represents avalue that would be achieved if there was ideal compliance to dosage andideal compliance to time. This metric allows for contextualization ofpatient behavior in light of the prescribed medication regimen. An idealpatient should have equal values for both the daily regimen adherencevalue and the daily regimen baseline value.

As an example, a maximum value is assumed for DAC in DDA=DAC×DIF. Thenthe newly calculated DDAs are summed as in the case of calculating DRAfor calculating the daily regimen baseline value (DRB).

In step 214, method 200 includes determining a medication adherencevalue (DA) based on the daily regimen adherence value and the dailyregimen baseline value. For example, a ratio of the daily regimenadherence value and the daily regimen baseline value may serve as themedication adherence value. In instances, the determined ratio may bemultiplied by a constant factor to ensure that the medication adherencevalue (DA) is an integer. For example, the following equation may beutilized:

DA=(DRA/DRB)×10

Accordingly, as an example if the DRA is 7 and the DRB is 10, themedical adherence value will be 7

In step 216, method 200 includes comparing the medication adherence witha threshold value. A threshold value may be set for a level where theclinical medical intervention may be necessary. For example, if amedical adherence value under 8 may have short-term or long-termconsequences, than a threshold value of 8 may be set. This value may beset by a physician, based on clinical data, application of learningalgorithms on clinical data (whether the patient's or broader set ofpatients), or a function of a combination of a physician'srecommendations along with clinical data.

In additional embodiments, multiple threshold values may be set to whichthe medical adherence value is compared. For example, a first thresholdvalue may be a critical value which represents a serious lapse inadherence, which requires urgent intervention. A second threshold valuemay be an adherence value which is not critical but still of medicalconcern. For example, on a scale of 0-10, a value of 3 may be a criticalvalue under which the adherence value must not drop. If it does, thenthe patient may require serious immediate care. On the other hand, avalue of 8 may be significant enough to require investigation ofpossible intervention.

In step 218, method 200 includes generating a notification when themedial adherence value is less than the threshold value. In detail, onceit is determined that the medication adherence value is less than thethreshold value a notification may be generated that may be thenprovided to the patient or other concerned entities such as pharmacists,physicians, and clinicians, etc. The notifications may serve asreminders as well as instruments to force reconsideration of treatmentplans and interventions.

In additional embodiments, medication adherence may be calculated forsuccessive days. Thereafter, processor 110 may then calculate avariation of the medical adherence over successive days. A rise or dropover a threshold amount on successive days may also trigger anotification, since the rise or drop may indicate that a patient is notmaintaining a stabilized dosage. The notification may prompt anintervention including prompting another literacy survey, in response towhich a physician may personally intervene.

While the method 200 is explained with respect to a daily time period,the same principles may be applied to calculate a medical adherence forany user-selected time period including a week; a month, etc. Theprinciple of the present disclosure may be used to monitor patientadherence to any medical regimen, including but not limited to,diagnostic testing, exercise, diet, etc.

In further embodiments, medical adherence values may be utilized incombination with other such self-management scores to obtain an overallhealth management score. Analytics framework may provide relationshipsbetween such scores for a patient, in order to identify violatingparameters and correct them—all with the use of a single dashboarddisplaying these scores. Hence, exemplary embodiments aid in reducingthe time for customers and physicians to make decisions about clinicalissues, as well as enhancing accuracy of clinical decisions. Embodimentsof the present disclosure are disease and population size agnostic, andtherefore have applicability across the spectrum of healthcare matters.

In some embodiments, data related to a patient's medical adherence maybe parsed and cleansed to comply with HIPPA privacy guidelines.Thereafter, the data may be provided to pharmaceutical companies orother entities to use behavioral data to modify their products and/orrecommendations.

In additional embodiments, in addition to providing a physicianinformation about a patient's medical adherence, modeling systems basedon user behavior may be utilized to provide treatment recommendations tophysicians. For example, providing suggesting to physician regardingmedication that have a high level of medical adherence.

The examples described above with respect to FIGS. 1-5, or any part(s)or function(s) thereof, may be implemented using hardware, softwaremodules, firmware, tangible computer readable media having instructionsstored thereon, or a combination thereof and may be implemented in oneor more computer systems or other processing systems.

FIG. 6 illustrates a high-level functional block diagram of an exemplarycomputer system 600, in which embodiments of the present disclosure, orportions thereof, may be implemented, e.g., as computer-readable code.For example, each of the exemplary devices and systems described abovewith respect to FIG. 1 can be implemented in computer system 600 usinghardware, software, firmware, tangible computer readable media havinginstructions stored thereon, or a combination thereof and may beimplemented in one or more computer systems or other processing systems.Hardware, software, or any combination of such may embody any of themodules and components in FIG. 1, as described above.

If programmable logic is used, such logic may be executed on acommercially available processing platform or a special purpose device.One of ordinary skill in the art may appreciate that embodiments of thedisclosed subject matter can be practiced with various computer systemconfigurations, including multi-core multiprocessor systems,minicomputers, mainframe computers, computers linked or clustered withdistributed functions, as well as pervasive or miniature computers thatmay be embedded into virtually any device.

For instance, at least one processor device and a memory may be used toimplement the above-described embodiments. A processor device may be asingle processor, a plurality of processors, or combinations thereof.Processor devices may have one or more processor “cores.”

Various embodiments of the present disclosure, as described above in theexamples of FIGS. 1-5 may be implemented using computer system 60E.After reading this description, it will become apparent to a personskilled in the relevant art how to implement embodiments of the presentdisclosure using other computer systems and/or computer architectures.Although operations may be described as a sequential process, some ofthe operations may in fact be performed in parallel, concurrently,and/or in a distributed environment, and with program code storedlocally or remotely for access by single or multi-processor machines. Inaddition, in some embodiments the order of operations may be rearrangedwithout departing from the spirit of the disclosed subject matter.

As shown in FIG. 6, computer system 600 includes a central processingunit (CPU) 620. CPU 620 may be any type of processor device including,for example, any type of special purpose or a general-purposemicroprocessor device. As will be appreciated by persons skilled in therelevant art, CPU 620 also may be a single processor in amulti-core/multiprocessor system, such system operating alone, or in acluster of computing devices operating in a cluster or server farm. CPU620 may be connected to a data communication infrastructure 610, forexample, a bus, message queue, network, or multi-core message-passingscheme.

Computer system 600 also may include a main memory 640, for example,random access memory (RAM), and also may include a secondary memory 630.Secondary memory 630, e.g., a read-only memory (ROM), may be, forexample, a hard disk drive or a removable storage drive. Such aremovable storage drive may comprise, for example, a floppy disk drive,a magnetic tape drive, an optical disk drive, a flash memory, or thelike. The removable storage drive in this example reads from and/orwrites to a removable storage unit in a well-known manner. The removablestorage unit may comprise a floppy disk, magnetic tape, optical disk,etc. which is read by and written to by the removable storage drive. Aswill be appreciated by persons skilled in the relevant art, such aremovable storage unit generally includes a computer usable storagemedium having stored therein computer software and/or data.

In alternative implementations, secondary memory 630 may include othersimilar means for allowing computer programs or other instructions to beloaded into computer system 600. Examples of such means may include aprogram cartridge and cartridge interface (such as that found in videogame devices), a removable memory chip (such as an EPROM, or PROM) andassociated socket, and other removable storage units and interfaces,which allow software and data to be transferred from a removable storageunit to computer system 600.

Computer system 600 also may include a communications interface (“COM”)560. Communications interface 660 allows software and data to betransferred between computer system 600 and external devices.Communications interface 660 may include a mode a network interface(such as an Ethernet card), a communications port, a PCMCIA slot andcard, or the like. Software and data transferred via communicationsinterface 660 may be in the form of signals, which may be electronic,electromagnetic, optical, or other signals capable of being received bycommunications interface 660. These signals may be provided tocommunications interface 660 via a communications path of computersystem 600, which may be implemented using, for example, wire or cable,fiber optics, a phone line, a cellular phone link, an RF link or othercommunications channels.

The hardware elements, operating systems, and programming languages ofsuch equipment are conventional in nature, and it is presumed that thoseskilled in the art are adequately familiar therewith. Computer system600 also may include input and output ports 650 to connect with inputand output devices such as keyboards, mice, touchscreens, monitors,displays, etc. Of course, the various server functions may beimplemented in a distributed fashion on a number of similar platforms,to distribute the processing load. Alternatively, the servers may beimplemented by appropriate programming of one computer hardwareplatform.

Program aspects of the technology may be thought of as “products” or“articles of manufacture” typically in the form of executable codeand/or associated data that is carried on or embodied in a type ofmachine-readable medium. “Storage” type media include any or all of thetangible memory of the computers, processors or the like, or associatedmodules thereof, such as various semiconductor memories, tape drives,disk drives and the like, which may provide non-transitory storage atany time for the software programming. All or portions of the softwaremay at times be communicated through the Internet or various othertelecommunication networks. Such communications, for example, may enableloading of the software from one computer or processor into another, forexample, from a management server or host computer of the mobilecommunication network into the computer platform of a server and/or froma server to the mobile device. Thus, another type of media that may bearthe software elements includes optical, electrical and electromagneticwaves, such as used across physical interfaces between local devices,through wired and optical landline networks and over various air-links.The physical elements that carry such waves, such as wired or wirelesslinks, optical links, or the like, also may be considered as mediabearing the software. As used herein, unless restricted tonon-transitory, tangible “storage” media, terms such as computer ormachine “readable medium” refer to any medium that participates inproviding instructions to a processor for execution.

It would also be apparent to one of skill in the relevant art that thepresent disclosure, as described herein, can be implemented in manydifferent embodiments of software, hardware, firmware, and/or theentities illustrated in the figures. Any actual software code with thespecialized control of hardware to implement embodiments is not limitingof the detailed description. Thus, the operational behavior ofembodiments will be described with the understanding that modificationsand variations of the embodiments are possible, given the level ofdetail presented herein.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the disclosed embodiments, as claimed.

Other embodiments of the disclosure will be apparent to those skilled inthe art from consideration of the specification and practice of theinvention disclosed herein. It is intended that the specification andexamples be considered as exemplary only, with a true scope and spiritof the invention being indicated by the following claims.

1. A computer-implemented method for managing a patient's medicaladherence, the method comprising: receiving, using a processor, datarelated to the patient, the data including information related to aprescribed medication regimen having one or more medications, patientbehavior data, a respective literacy level associated with each of theone or more medications; calculating a compliance to dosage and acompliance to time for each of the one or more medications based on thereceived data; calculating a drug adherence count associated with eachof the one or more medications by summing at least two of the complianceto dosage, the compliance to time, and the respective literacy levelassociated with each of the one or more medications; determining a dailymedication adherence for each of the one or more medications;calculating a daily regimen adherence value by summing the dailymedication adherence of all of the one or more medications in themedication regimen; calculating a daily regimen baseline value byre-calculating the daily regimen adherence value by utilizing a maximumpotential value for the drug adherence count for each of the respectivemedications in the regimen associated with the patient; determining amedical adherence value based on the daily regimen adherence value andthe daily regimen baseline value; and comparing the medical adherencewith a threshold value. 2-27. (canceled)